1. Image Preparation for Convolutional Neural Network with TensorFlow's Keras API

The images included in the data/skin-cancer directory are a random subset of microscopic images of Benign & Malignant Skin Cancer cells from ISIC Data-Base: https://www.isic-archive.com/#!/topWithHeader/onlyHeaderTop/gallery

2. Create a Convolutional Neural Network with TensorFlow's Keras API

3. Train a Convolutional Neural Network with TensorFlow's Keras API

4. Build a Test Set with TensorFlow's Keras API

5. Neural Network Predictions with TensorFlow's Keras API

6. Create a Confusion Matrix for Neural Network Predictions

7. Create a Classification Report for Neural Network Predictions

8. Deployment of the Convolutional Neural Network

9. Save and Load a Model with TensorFlow's Keras API

1. model.save()

This save functions saves:

  1. The architecture of the model allowing to re-create the moddel.
  2. The weights of the model.
  3. The training configuration (loss, optimizer).
  4. The state of the optimizer, allowing to resume training exactly where you left off.

2. model.to_json()

if you only need to save architecture of a model, and not its weights or its training configuration, you can see the following function to save the architecture only.

3. model.save_weights()

If you only need to save the weights of the model, you cab use the following function save the weights only.

10. Clean and Delete all the Directories